It is widely appreciated that environmental stresses, such as exposure to toxins or pathogens, can have profound impact on individual health and well-being. How these "stressors" exert their influence is less well understood. While specific targets of environmental stresses have been identified for some toxins and pathogens, we propose that the impact of environmental stresses is mediated through the pathway(s) and/or networks in which the target molecule participates. Furthermore, even where a causal association between an environmental stress and a biological target has been identified, the biological insight that must precede a strategy for therapeutic intervention has generally been slow in coming. We suggest that the phenotypic effects of environmental stresses are mediated by alterations in a dynamic network of gene products and metabolites, and such networks, normal and perturbed, exhibit emergent properties that cannot be understood one gene at a time. Our central hypothesis is that one must understand changes in complex cellular networks to fully understand the link between genotype, environment, and phenotype. The Center for Cancer Systems Biology (CCSB) at the Dana-Farber Cancer Institute, together with a growing number of laboratories, is mapping and modeling cellular pathways and networks both "locally" at the scale of "molecular circuits" made of a few interacting molecules, and "globally" at the scale of the whole proteome;fundamental biological insights have already emerged from this body of work. We propose to use a model system as a surrogate for generalized environmental stresses to begin understanding how cellular pathways and networks are altered or modified as a consequence of environmental insult. We have chosen a defined, model system with a variety of disease outcomes: viral infection. Here we explore the concept that environmental stresses, as exemplified by viruses, influence local and global properties of networks to induce "disease states". Our plans to achieve these goals are summarized in the following specific aims: 1) Profile all binary viral-host protein-protein interactions for a group of viruses with related biological properties 2) Systematically test each viral protein for its ability to disrupt or alter host-host protein interactions, 3) Integrate the resulting interaction and perturbation data with diverse genomic data sources to derive dynamic cellular network models.